CN114222309A - Multi-machine cooperative ad hoc network method based on consent theory - Google Patents
Multi-machine cooperative ad hoc network method based on consent theory Download PDFInfo
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Abstract
The application belongs to the technical field of command and control, and particularly relates to a multi-machine cooperative ad hoc network method based on a consent theory. The method comprises the following steps: step one, constructing a multi-machine cooperative networking consent relation graph model based on a consent networking mechanism, and the method comprises the following steps: acquiring local communication requirements of each node for realizing overall network efficiency, and discretizing the local communication requirements; decomposing a data information flow which continuously passes through multiple hops in a network into promises of discrete nodes to peripheral nodes of the nodes, and publishing self intentions to other nodes by the nodes in a promises manner and meeting requirements mutually to obtain a multi-machine cooperative networking promises relation graph model; step two, defining a cashing mechanism of consent in the multi-machine cooperative networking consent relation graph model, wherein the cashing mechanism comprises the following steps: obtaining the value of the consent behavior among the nodes, wherein the value is the service quality level corresponding to the consent behavior; and establishing a reward and punishment mechanism of the bargained game based on the value of the consent action so that the consent can be honored.
Description
Technical Field
The application belongs to the technical field of command and control, and particularly relates to a multi-machine cooperative ad hoc network method based on a consent theory.
Background
When a complex environment is faced, isomorphic/heterogeneous platform nodes in a multi-machine cooperative data communication network may frequently perform high-speed maneuvering, and meanwhile, the situations of node damage, inter-node data link interruption and the like may be accompanied, nodes may be randomly added or withdrawn, and the inter-machine network topology is separated and split and randomly and rapidly changes. Therefore, a multi-node mobile ad hoc network strategy needs to be designed, and a multi-hop decentralization communication network with strong robustness is established to meet the requirement of multi-computer cooperative interaction operation.
The existing mobile node ad hoc network strategy usually selects to actively maintain a routing path during the node moving period or to start to passively discover a route when the nodes need to communicate, the implementation is based on that any node can orderly operate according to a plan, when the nodes move at high speed and the topology changes violently, the adaptive capacity to the state change of peripheral nodes is lacked, a large amount of manual intervention configuration operation is needed, the interaction of all data of each communication node is difficult to manage and control through manual intervention, the nodes are difficult to be controlled to be in preset configuration completely, so that the robustness of a multi-computer cooperative network is poor, and the dynamic autonomy and self-repair of the network are difficult to realize.
Accordingly, a technical solution is desired to overcome or at least alleviate at least one of the above-mentioned drawbacks of the prior art.
Disclosure of Invention
The application aims to provide a multi-machine cooperative ad hoc network method based on consent theory to solve at least one problem in the prior art.
The technical scheme of the application is as follows:
a multi-machine cooperative ad hoc network method based on consent theory comprises the following steps:
step one, constructing a multi-machine cooperative networking consent relation graph model based on a consent networking mechanism, and the method comprises the following steps:
acquiring local communication requirements of each node for realizing overall network efficiency, and discretizing the local communication requirements;
decomposing a data information flow which continuously passes through multiple hops in a network into promises of discrete nodes to peripheral nodes of the nodes, and publishing self intentions to other nodes by the nodes in a promises manner and meeting requirements mutually to obtain a multi-machine cooperative networking promises relation graph model;
step two, defining a cashing mechanism of consent in the multi-machine cooperative networking consent relation graph model, wherein the cashing mechanism comprises the following steps:
obtaining the value of the consent behavior among the nodes, wherein the value is the service quality level corresponding to the consent behavior;
and establishing a reward and punishment mechanism of the bargained game based on the value of the consent action so that the consent can be honored.
In at least one embodiment of the application, in a multi-machine cooperative networking consent graph model, the consent is defined as an autonomous declaration of the behavior of the nodes of the intelligent agent, each basic consent comprises a sending node S, a receiving node R and a consent principal pi, and the node S provides a topic b to the consent of the node R by the following expression:
in at least one embodiment of the present application, the attribute set of the sending node S and the receiving node R includes a node type, a number ID registered in the network by the node, a specific capability of the node in the network, and an consent form established by the node according to its own functional requirements for other types of nodes:
S/R::[Type,ID,Capacity,table]。
in at least one embodiment of the present application, the consent entity pi is a double composition (τ, χ), where τ is a consent type and χ is a constraint indicating a subset of possible values within the τ domain reserved by the proxy consent, characterized by a binary relationship of the sending node S and the receiving node R:
in at least one embodiment of the present application, the topic b represents some constraint, restriction, matching action, event or service.
In at least one embodiment of the present application, the consent types include a use consent, a conditional consent, and a collaborative consent, wherein,
the use promises are in the form of:
indicating that the sending node S promises to use service b to the receiving node R;
the conditional consent is in the form of:
represents the sending node S committing to complete b1 service for the receiving node R subject to event b 2;
the collaborative consent is in the form of:
indicating that the sending node S promises to do the same thing as the receiving node R on class b events, involving the two nodes following and imitating each other in the information transmission.
In at least one embodiment of the application, the reward and punishment mechanism for establishing the bargained game based on the value of the consent action enables the consent to be honored comprises:
based on the value of the consent behavior, an iterative bargaining game relation between nodes is established, and for the mutually consented node A and node B:
wherein v is a value;
the evaluation of the service quality level is completed by iterating the service quality level provided by the game node at the previous moment and the service quality level provided at the earlier moment:
v1(t+1)＝b2v2(t)v2(t-1)+a2v2(t)
v2(t+1)＝b1v1(t)v1(t-1)+a1v1(t)
obtaining the value change condition of the allowed behavior through iterative comparison at different moments, and establishing a reward and punishment mechanism according to the value change condition:
when the value of the consent behavior is lower and lower, defining the consent behavior as a selfish node, punishing the selfish node, and reducing the consent credit of the selfish node;
and when the consent reputation of the selfish node is reduced to a certain threshold value, the consent following probability of other nodes to the selfish node is reduced, and the network dynamic balance is realized.
In at least one embodiment of the present application, the method further includes a third step of calculating robustness of the multi-machine cooperative networking promotion graph model:
expressing the relation between any node in the multi-computer cooperative networking promised relation graph model and other nodes through a group of reliability assessment adjacency matrixes:
the adjacency matrix is represented as an nth-order square matrix A formed by linear combination of the following formulas:
wherein n is the number of nodes in the multi-machine cooperative networking promised relationship graph model;
the row and column values corresponding to no consent are 0.
The invention has at least the following beneficial technical effects:
according to the multi-machine cooperative ad hoc network method based on the consent theory, the thought of forced constraint on the communication relation between the nodes is replaced by a mutual consent mode between the nodes, a network which can still operate autonomously and cooperatively under the limits of capacity, conditions, environment and the like is established, and the problem of poor robustness of multi-machine cooperative networking in a high dynamic environment is solved.
Drawings
FIG. 1 is a flowchart of a multi-machine cooperative ad hoc network method based on consent theory according to an embodiment of the present application;
FIG. 2 is a diagram illustrating a task-oriented multi-machine cooperative networking consent relationship model according to an embodiment of the present application.
Detailed Description
In order to make the implementation objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are a subset of the embodiments in the present application and not all embodiments in the present application. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. Embodiments of the present application will be described in detail below with reference to the accompanying drawings.
In the description of the present application, it is to be understood that the terms "center", "longitudinal", "lateral", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are used merely for convenience in describing the present application and for simplifying the description, and do not indicate or imply that the referenced device or element must have a particular orientation, be constructed in a particular orientation, and be operated, and therefore should not be construed as limiting the scope of the present application.
The present application is described in further detail below with reference to fig. 1-2.
The application provides a multi-machine cooperative ad hoc network method based on a consent theory, which comprises the following steps:
s100, constructing a multi-machine cooperative networking consent relation graph model based on a consent networking mechanism, and comprising the following steps:
acquiring local communication requirements of each node for realizing overall network efficiency, and discretizing the local communication requirements;
decomposing a data information flow which continuously passes through multiple hops in a network into promises of discrete nodes to peripheral nodes of the nodes, and publishing self intentions to other nodes by the nodes in a promises manner and meeting requirements mutually to obtain a multi-machine cooperative networking promises relation graph model;
s200, defining a consent mechanism in the consent relationship graph model of the multi-machine cooperative networking, comprising the following steps:
obtaining the value of the consent behavior among the nodes, wherein the value is the service quality level corresponding to the consent behavior;
and establishing a reward and punishment mechanism of the bargained game based on the value of the consent action so that the consent can be honored.
According to the multi-machine cooperative ad hoc network method based on the consent theory, firstly, a multi-machine cooperative networking consent relation graph model is constructed based on the consent networking mechanism. Consent between nodes is defined as an express statement of a desired action to be performed by a node, such statement containing the body, quality/quantity, trustworthiness and other characteristics of the desired state. All independent and autonomous nodes in the model can form expectations of mutual cooperation behaviors through mutual consent, and then a complete end-to-end working system is established. If the mutual consent relationship between the nodes can be established according to what information each node in the autonomous collaborative network expects to acquire from the network, the operation of all the nodes through manual intervention under a high dynamic environment can be reduced, the collapse probability of the whole network when the network nodes can not address logic according to the preset communication route is reduced, and the forced communication rule compliance of each node is changed into voluntary collaboration.
In the preferred embodiment of the application, in the multi-machine cooperative networking promotion graph model, promotion is defined as an autonomous declaration of intelligent agent node behaviors, each basic promotion comprises a sending node S, a receiving node R and a promotion main body pi, and the following formula represents that the node S provides a theme b to the promotion of the node R:
the attribute set of the sending node S and the receiving node R includes a node type, a number ID registered in the network by the node, a specific capability of the node in the network, and an consent form (including services that can be provided and services that need to be accepted) established by the node according to its functional requirements for other types of nodes:
S/R::[Type,ID,Capacity,table]。
the consent entity pi describes the topic b of consent, specifying what is specifically agreed upon, usually a double combination (τ, χ), where τ is the consent type and χ is the constraint indicating the subset of possible values within the τ domain reserved by the agent consent, characterized by the binary relationship of the sending node S and the receiving node R:
topic b represents some constraint, restriction, matching behavior, event, or service.
According to the multi-machine cooperation ad hoc network method based on the consent theory, when a consent relationship network is constructed, local communication requirements of each node for realizing overall network efficiency are firstly analyzed, a plurality of local requirements are discretized, a data information flow continuously passing through a plurality of hops in the network is disassembled into consent of discrete nodes to peripheral nodes of the discrete nodes, the nodes publish self intention to other nodes in a consent mode and mutually meet the requirements, and corresponding service contracts such as cooperation, use and conditions are established according to the consent. And establishing a consent relation table for peripheral nodes at each node, considering that the communication between the two nodes meets the overall requirement when the consent is complied with the cashing, and finishing effective interaction of information between the nodes in a mode of continuously cashing the consent.
In this embodiment, the consent type applied to the inter-node networking communication is designed as follows:
TABLE 1
The logic of the process is essentially to transfer the overall expectation or target of the network global to a certain area or a certain node in the network, and preset the behavior of all the nodes as the probability attribute of the intelligent agent according to the intention of the intelligent agent, and describe the operation logic of the network overall through the discretization spontaneous consent of each node. Each node must fulfill its consent by using its forward consent to ensure that it adheres to dependencies in the network.
The system attributes of the promised network can be combined and analyzed by using a graphic language, the communication topological connection among multiple nodes is abstracted into promised information flow, and a promised relation graph is further obtained, wherein the promised relation graph is equivalent to discretizing each node of the whole communication network, the final addressing routing target of a certain node is not concerned any more, and only the communication promises made to adjacent nodes are considered.
And allocating a consent list to other nodes for each class of nodes according to the communication requirements of the nodes, and searching each object node according to the consent list and publishing the intention and address information of the object node immediately after the nodes join in network registration. When the target neighbor node is damaged and exits the network, the source node searches for a consent relation with other neighbor nodes established according to the same intention according to the consent table, and address information and the like required by addressing transmission among the nodes are contained in consent main body information, and finally, the dynamic closed-loop operation of the whole network is realized.
In an embodiment of the application, for multi-machine cooperation, if the whole airplane is taken as a node, the promised information amount required by the node is too large, so that the task-oriented discretization of each function of the airplane platform is considered, various computing devices, sensors and the like are taken as independent functional nodes to be embedded into a promised model, and a multi-machine cooperation networking promised relation graph model of a certain task scene is established according to the theory, as shown in fig. 2. The model comprises a plurality of functional nodes which are divided into detection O, strike F, interference S and command type nodes C, wherein T represents a target node. R represents the promised relationship between the nodes,
the command node C promises to issue a striking instruction to a striking node F, and the F promises to execute the striking instruction after receiving and returns a damage evaluation result to the C;
the commanding node C promises to issue a probing instruction to a probing node O, and the O promises to execute the probing instruction and return a probing result to the C after receiving;
the command node C promises to issue an electronic interference instruction to an interference node S, and the S promises to execute electronic interference and return a load state to the C after receiving; rcRepresenting cooperative exploration, attack consent relationships between nodes of the same type (cooperative consent type);
representing the promises of detecting, striking and electronic interference to the preset or random target nodes.
In the multi-machine cooperative self-networking method based on the consent theory, secondly, a consent mechanism of consent in a multi-machine cooperative networking consent relationship graph model needs to be defined. Whether the consent is honored is crucial to reliability of networking, partial selfish nodes may exist in the consent network, in order to achieve maximization of pursuit of self 'demand', under the condition of lack of an effective node reward punishment strategy, a part of the consent may not be honored, and lack of the part of data forwarding may cause consent of other nodes to be unable to be honored. Because each communication node in the network has no prior cooperative obligation, the corresponding reward and punishment mechanism is established by adopting a method of bargaining game among the nodes to realize autonomous cooperation, and the promised result can be regarded as a steady-state balance result after the game among the nodes.
The premise of carrying out the bargaining game among the nodes is that the promissory behavior needs to have value, the service quality and reliability provided by the promissory function within the duration of promissory being followed, namely within the service contract agreement validity period are defined as the value of the promissory behavior, and only the promissory receiver can realize the value. The consent recipient may measure value for the offered one or more consent in terms of perceived reliability. The value may motivate the nodes to comply with the redemption consent in the game, promoting the reliability of the consent network.
In a preferred embodiment of the present application, establishing a reward and punishment mechanism of a bargained game based on the value of the consent action enables the consent to be honored comprises:
based on the value of the consent behavior, an iterative bargaining game relation between nodes is established, and for the mutually consented node A and node B:
wherein v is a value;
the evaluation of the service quality level is completed by iterating the service quality level provided by the game node at the previous moment and the service quality level provided at the earlier moment:
v1(t+1)＝b2v2(t)v2(t-1)+a2v2(t)
v2(t+1)＝b1v1(t)v1(t-1)+a1v1(t)
obtaining the value change condition of the allowed behavior through iterative comparison at different moments, and establishing a reward and punishment mechanism according to the value change condition:
when the value of the consent behavior is lower and lower, defining the consent behavior as a selfish node, punishing the selfish node, and reducing the consent credit of the selfish node;
and when the consent reputation of the selfish node is reduced to a certain threshold value, the consent following probability of other nodes to the selfish node is reduced, and the network dynamic balance is realized.
In this embodiment, if the node B promises to forward the message of the neighboring node a to the neighboring node C, the message that the node a has sent out may be cached, the forwarding content of the node B may be monitored and compared with the cache, if the forwarding content of the node B conforms to the cache, the node B completes forwarding, the change condition of the service level quality of the promissory behavior is determined through iterative comparison at different times, a reward and punishment mechanism is established according to the change condition of the value, when the promissory behavior has a lower value, it is determined that the node B does not comply with the promissory behavior, the node B is defined as a selfish node, corresponding punishment is performed on the selfish node, and the promissory reputation of the node B is reduced. And configuring a dynamic adjusting module for gradually increasing the promised reputation of each intelligent node of the promised network, wherein if the promised reputation of the source node is reduced to a certain threshold value, the adjacent nodes also reduce the promised following probability of the source node, and finally, the network dynamic balance is realized.
Further, the multi-machine cooperative ad hoc network method based on the consent theory comprises the step of S300 calculating the robustness of the consent relationship graph model of the multi-machine cooperative networking.
A method of quantitatively calculating a probability of consent being followed in a network may be established based on graph theory, where consent of a source node has certain continuity characteristics, and the function of consent probabilistically exerts an influence on other nodes along each link in the network. The method comprises the steps that any node in the promo network can represent the relation with other nodes through a group of adjacency matrixes, if an iterative game linear calculation relation for promo service level evaluation among the adjacent nodes is established, the linear calculation relations are integrated to form a reliability evaluation adjacency matrix, the overall judgment basis of the promo network reliability can be obtained from the perspective of graph theory, and then the network robustness criterion under the conditions of node damage and the like is obtained.
In this embodiment, an arbitrary node in the multi-machine cooperative networking consent relationship graph model represents a relationship with other nodes through a set of reliability assessment adjacency matrices:
the adjacency matrix is represented as an nth-order square matrix A formed by linear combination of the following formulas:
wherein n is the number of nodes in the multi-machine cooperative networking promised relationship graph model;
the row and column values corresponding to no consent are 0.
The larger the matrix eigenvalue is, the stronger the robustness is.
The multi-computer cooperative ad hoc network method based on the consent theory considers each dynamic communication node in the multi-computer cooperative network as an intelligent individual (Agent), tries to form a service contract through mutual consent among the nodes instead of forcibly issuing the requirements on the communication content and the routing addressing path of each node, and realizes the ad hoc network which supports the nodes to join and quit at random without excessive manual intervention configuration under a high dynamic environment.
The multi-machine collaborative ad hoc networking method based on the consent theory has the advantages that a new thought for realizing multi-node dynamic networking based on mutual consent is conceived, compared with the existing dynamic ad hoc networking method, all communication multi-hop paths of all nodes in a network are prevented from being defined and controlled in a centralized mode, each node forms a service contract with adjacent nodes according to self requirements, consent and punishment mechanisms of bargaining game are established to enable consent to be honored, dynamic balance is realized, and finally an autonomous collaborative network with strong robustness is constructed. Besides the cooperation of multiple machines, the method can be expanded to other application scenes such as unmanned vehicles and the like which need dynamic networking communication.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. A multi-machine cooperative ad hoc network method based on consent theory is characterized by comprising the following steps:
step one, constructing a multi-machine cooperative networking consent relation graph model based on a consent networking mechanism, and the method comprises the following steps:
acquiring local communication requirements of each node for realizing overall network efficiency, and discretizing the local communication requirements;
decomposing a data information flow which continuously passes through multiple hops in a network into promises of discrete nodes to peripheral nodes of the nodes, and publishing self intentions to other nodes by the nodes in a promises manner and meeting requirements mutually to obtain a multi-machine cooperative networking promises relation graph model;
step two, defining a cashing mechanism of consent in the multi-machine cooperative networking consent relation graph model, wherein the cashing mechanism comprises the following steps:
obtaining the value of the consent behavior among the nodes, wherein the value is the service quality level corresponding to the consent behavior;
and establishing a reward and punishment mechanism of the bargained game based on the value of the consent action so that the consent can be honored.
2. The multi-machine cooperative ad hoc network method based on consent theory according to claim 1, wherein in the multi-machine cooperative networking consent relationship graph model, the consent is defined as an autonomous declaration of the intelligent agent node behavior, each basic consent comprises a sending node S, a receiving node R and a consent principal pi, and the node S provides a topic b to the node R consent expressed by the following formula:
3. the multi-machine cooperative ad hoc network method based on consent theory according to claim 2, wherein the attribute set of the sending node S and the receiving node R comprises node type, number ID of the node registered in the network, specific capability of the node in the network, and consent tables established by the node according to its own functional requirements for other types of nodes:
S/R::[Type,ID,Capacity,table]。
4. the consent-theory based multi-machine cooperative ad hoc network method, according to claim 3, wherein the consent entity pi is a double combination (τ, χ), wherein τ is a consent type and χ is a constraint indicating a subset of possible values within τ field reserved by proxy consent, characterized by a binary relationship between the sending node S and the receiving node R:
5. a consent-theory based multi-machine collaborative ad hoc network method according to claim 4, wherein the topic b represents some constraint, limitation, matching behavior, event or service.
6. The consent-theory based multi-machine collaborative ad hoc network method of claim 5, wherein the consent types include use consent, conditional consent, and collaborative consent, wherein,
the use promises are in the form of:
indicating that the sending node S promises to use service b to the receiving node R;
the conditional consent is in the form of:
represents the sending node S committing to complete b1 service for the receiving node R subject to event b 2;
the collaborative consent is in the form of:
indicating that the sending node S promises to do the same thing as the receiving node R on class b events, involving the two nodes following and imitating each other in the information transmission.
7. The multi-machine cooperative ad hoc network method based on the consent theory according to claim 6, wherein the creating a reward and punishment mechanism of a bargained game based on the value of the consent action so that the consent can be honored comprises:
based on the value of the consent behavior, an iterative bargaining game relation between nodes is established, and for the mutually consented node A and node B:
wherein v is a value;
the evaluation of the service quality level is completed by iterating the service quality level provided by the game node at the previous moment and the service quality level provided at the earlier moment:
v1(t+1)＝b2v2(t)v2(t-1)+a2v2(t)
v2(t+1)＝b1v1(t)v1(t-1)+a1v1(t)
obtaining the value change condition of the allowed behavior through iterative comparison at different moments, and establishing a reward and punishment mechanism according to the value change condition:
when the value of the consent behavior is lower and lower, defining the consent behavior as a selfish node, punishing the selfish node, and reducing the consent credit of the selfish node;
and when the consent reputation of the selfish node is reduced to a certain threshold value, the consent following probability of other nodes to the selfish node is reduced, and the network dynamic balance is realized.
8. The multi-machine cooperative ad hoc network method based on consent theory according to claim 7, further comprising the step three of calculating robustness of the multi-machine cooperative networking consent relationship graph model:
expressing the relation between any node in the multi-computer cooperative networking promised relation graph model and other nodes through a group of reliability assessment adjacency matrixes:
the adjacency matrix is represented as an nth-order square matrix A formed by linear combination of the following formulas:
wherein n is the number of nodes in the multi-machine cooperative networking promised relationship graph model;
the row and column values corresponding to no consent are 0.
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| CN103152788A (en) * | 2013-02-21 | 2013-06-12 | 湖南大学 | Game-based VMIMO (Virtual Multiple Input Multiple Output) cooperative routing method |
| CN113613257A (en) * | 2021-07-16 | 2021-11-05 | 中国空间技术研究院 | Game theory-based sensor network self-organizing cooperative k covering method |
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